Confirmatory and bi-factor analysis of the Short Form Health Survey 8 (SF-8) scale structure in a German general population sample.

BACKGROUND: The SF-8 is a short form of the SF-36 Health Survey, which is used for generic assessment of physical and mental aspects of health-related quality of life (HRQoL). Each of the 8 dimensions of the SF-36 is covered by a single item in the SF-8. The aim of the study was to examine the latent model structure of the SF-8. METHOD: One-, two- and three dimensional as well as bi-factor structural models were defined and estimated adopting the ML- as well as the WLSMV-algorithm for ordinal data. The data were collected in a German general population sample (N = 2545 persons). RESULTS: A two- (physical and mental health) and a three-dimensional CFA structure (in addition overall health) represent the empirical data information adequately [CFI = .987/.995; SRMR = .024/.014]. If a general factor is added, the resulting bi-factor models provide a further improvement in data fit [CFI = .999/.998; SRMR = .001]. The individual items are much more highly associated with the general HRQoL factor (loadings: .698 to .908) than with the factors physical, mental, and overall health (loadings: -.206 to .566). CONCLUSIONS: In the SF-8, each item reflects mainly general HRQoL (general factor) as well as one of the three components physical, mental, and overall health. The findings suggest in particular that the evaluation of the information of the SF-8 items can be validly supplemented by a general value HRQoL.

[Application and Integration of Qualitative and Quantitative Research Methods in Intervention Studies in Rehabilitation Research]. / Anwendung und Integration qualitativer und quantitativer Forschungsmethoden in der rehabilitationswissenschaftlichen Interventionsforschung.

In order to develop and evaluate interventions in rehabilitation research a wide range of empirical research methods may be adopted. Qualitative research methods emphasize the relevance of an open research focus and a natural proximity to research objects. Accordingly, using qualitative methods special benefits may arise if researchers strive to identify and organize unknown information aspects (inductive purpose). Particularly, quantitative research methods require a high degree of standardization and transparency of the research process. Furthermore, a clear definition of efficacy and effectiveness exists (deductive purpose). These paradigmatic approaches are characterized by almost opposite key characteristics, application standards, purposes and quality criteria. Hence, specific aspects have to be regarded if researchers aim to select or combine those approaches in order to ensure an optimal gain in knowledge.